Difference In Mean Time Research Articles

Placebo-controlled efficacy of 17 anti-anginal drugs and percutaneous coronary intervention for first-line treatment of stable angina: systematic review & meta-analysis of 5153 patients from 53 trials

Abstract Background Percutaneous coronary intervention (PCI) for stable angina is currently recommended for patients with residual symptoms despite maximal anti-anginal medication. Placebo-controlled data demonstrating efficacy of PCI has recently become available. Purpose We evaluated the placebo-controlled efficacy of anti-anginal agents and PCI, as monotherapies for stable angina. Methods We performed a systematic review and meta-analysis of placebo-controlled randomised controlled trials (RCTs) of anti-anginal agents (17 medications across 7 drug classes [beta-blocker, dihydropyridine (DHP) calcium channel blocker (CCB), non-DHP CCB, ivabradine, nicorandil, nitrates and ranolazine]), and PCI, which reported the placebo-controlled treatment effect on standardised exercise duration in patients with stable angina, who were receiving no background anti-anginal medications. We searched MEDLINE, EMBASE, and Cochrane CENTRAL from database inception to 01 December 2023. Relevant systematic reviews and reference lists were inspected to identify publications which had not been identified in the primary searches. Two independent reviewers extracted the data and assessed the risk of bias of included studies. Intention-to-treat data were used. Meta-analyses were carried out using random-effects methods and reported using the PRISMA guidelines. The primary outcome was mean difference in total exercise time with treatment compared with placebo. A pairwise comparison of all anti-anginal medications and PCI was performed to evaluate their relative placebo-controlled efficacy on total exercise time. Results A total of 52 trials were eligible, evaluating 83 treatment arm comparisons of anti-anginal monotherapy (2408 patients) and placebo (2444 patients). The number of trials per medication class ranged from one (ivabradine) to 19 (non-DHP CCBs). All classes improved exercise time compared to placebo, with mean increment ranging from 22.4 seconds (95% confidence interval, 0.8 to 44.0, p=0.04) for ranolazine, to 76.5 seconds (63.2 to 89.8, p<0.0001) for DHP CCBs (Figure 1). There was substantial heterogeneity in exercise time increment between drug classes (I2 98%, p<0.0001). However, across all classes, there was a clear dose-response relationship (b-coefficient 24.8, 15.8 to 33.9, <0.0001). The only trial which compared PCI (151 patients) to placebo (150 patients) showed a placebo-controlled exercise duration increment of 59.5 seconds (16 to 103, P=0.001). This was comparable to the global mean effect across all anti-anginal medications (59, 39 to 79, P<0.0001). Conclusions Each anti-anginal drug class showed a clear increase in placebo-controlled exercise time, with varying effect sizes between classes. The DHP CCB class showed the largest effect size, and ivabradine and ranolazine showed the smallest. The effect of PCI monotherapy was similar to the mean anti-anginal medication monotherapy effect.Figure 1

Subcutaneous fast-acting insulin analogues ± long-acting insulin vs IV insulin infusion in DKA: updated meta-analysis of randomised trials.

Diabetic ketoacidosis (DKA) is often treated with intravenous regular insulin infusion (IVRII). Subcutaneous fast-acting insulin analogues (FAIAs); either alone or combined with subcutaneous long-acting insulin (LAI); might be useful to treat DKA. Our meta-analysis updated on their benefits and safety in DKA. We searched major electronic databases for randomised trials on subcutaneous FAIAs ± subcutaneous LAI vs IVRII in DKA. Primary outcomes were all-cause in-hospital mortality, time to resolution of DKA and hyperglycemia, in-hospital DKA recurrence and hospital readmission for DKA post-discharge. Secondary outcomes included resource utilisation and patient satisfaction. Safety outcomes were adverse events. Reviewers assessed risk of bias and quality of evidence using GRADE. We performed a priori subgroup and trial sequential analyses on primary outcomes. Seven trials enrolled 351 mainly adult patients (255/351) with mild to moderate DKA. No trials studied subcutaneous FAIA and subcutaneous LAI. Their risk of bias was high or unclear in several domains. No all-cause in-hospital mortality and DKA recurrence were reported. No trial investigated hospital readmission for DKA post-discharge. There was no difference in mean time to resolution of DKA (mean difference = -0.70, 95% CI -2.18 to 0.79 h, p = 0.36) or hyperglycemia [blood glucose < 250 mg/dL (13.9 mmol/L)] (mean difference = -0.17, 95% CI -1.10 to 0.76 h, p = 0.72) between subcutaneous FAIA and IVRII groups. There were largely no subgroup effects. Both groups had similar secondary outcomes. Hypoglycemia was the most common adverse event. Quality of evidence was low to very-low for all outcomes. The only possible trial sequential analysis for time to resolution of DKA was inconclusive. There was low- to very-low quality evidence that subcutaneous FAIA did not affect patient-centered outcomes in mainly adult patients with mild to moderate DKA compared to IVRII.

Time to Publication in Medical Education Journals: An Analysis of Publication Timelines During COVID-19 (2019-2022).

COVID-19 changed scholarly publishing. Yet, its impact on medical education publishing is unstudied. Because journal articles and their corresponding publication timelines can influence academic success, the field needs updated publication timelines to set evidence-based expectations for academic productivity. This study attempts to answer the following research questions: did publication timelines significantly change around the time of COVID-19 and, if so, how? We conducted a bibliometric study; our sample included articles published between January 2018, and December 2022, that appeared in the Medical Education Journals List-24 (MEJ-24). We clustered articles into three time-based groups (pre-COVID, COVID-overlap, and COVID-endemic), and two subject-based groups (about COVID-19 and not about COVID-19). We downloaded each article's metadata from the National Library of Medicine and analyzed data using descriptive statistics, analysis of variance, and post-hoc tests to compare mean time differences across groups. Overall, time to publish averaged 300.8 days (SD = 200.8). One-way between-groups ANOVA showed significant differences between the three time-based groups F (2, 7473) = 2150.7, p < .001. The post-hoc comparisons indicated that COVID-overlap articles took significantly longer (n = 1470, M= 539; SD = 210.6) as compared to pre-COVID (n = 1281; M = 302; SD = 172.5) and COVID-endemic articles (n = 4725; M = 226; SD = 136.5). Notably, COVID-endemic articles were published in significantly less time than pre-pandemic articles, p < .001. Longer publication time was most pronounced for COVID-overlap articles. Publication timelines for COVID-endemic articles have shortened. Future research should explore how the shift in publication timelines has shaped medical education scholarship.

Comparison of oral caffeine and oral theophylline for apnea of prematurity: A randomized clinical trial

Background Caffeine and theophylline are methylxanthine compounds that have been widely used in the treatment of apnea of prematurity (AOP). Previous studies comparing the two agents have shown inconsistent results and have mostly used intravenous preparations. Objective To assess the effectiveness of oral administration of caffeine compared to oral theophylline as therapy for apnea of prematurity. Methods Fifty consecutively recruited premature neonates (gestational age 28-34 weeks, birth weight &lt;2,500 g) with AOP who were able to tolerate at least 10 mL/kg of enteral feeding were randomized to receive either oral caffeine or oral theophylline for seven days. The main outcome was the daily frequency of apnea after treatment. Secondary outcomes were duration of oxygen or CPAP administration, duration of oxygen fraction (FiO2) taper to reach 21%, time to achievement of full feeding tolerance, length of hospital stay, and side effects. Results We randomized 25 subjects into each group. The distribution of baseline characteristics (gender, gestational age, mode of delivery, birth weight and length, age at onset of AOP, and initial frequency of AOP) was similar between both groups. The mean daily number of apnea episodes after treatment was significantly higher in the caffeine group compared to the theophylline group [3.16 (SD 1.31) vs. 2.28 (SD 1.40); P=0.031]. The caffeine group, compared to the theophylline group, also had a longer mean duration of oxygen or CPAP use [12.56 (SD 7.67) days vs. 8.40 (SD 6.41) days; P=0.030] and duration of FiO2 taper [5.76 (SD 2.68) vs. 4.08 (SD 2.54); P=0.035]. There were no significant differences in mean time to full feeding and mean length of hospital stay. There was no significant difference in the occurrence of side effects between the two groups. Conclusion In premature neonates with AOP, oral theophylline is slightly more effective than oral caffeine in reducing the frequency of apnea and is associated with a shorter duration of oxygen or CPAP use and duration to reach 21% FiO2.

Deep Learning-Based Real-Time Organ Localization and Transit Time Estimation in Wireless Capsule Endoscopy.

Wireless capsule endoscopy (WCE) has significantly advanced the diagnosis of gastrointestinal (GI) diseases by allowing for the non-invasive visualization of the entire small intestine. However, machine learning-based methods for organ classification in WCE often rely on color information, leading to decreased performance when obstacles such as food debris are present. This study proposes a novel model that integrates convolutional neural networks (CNNs) and long short-term memory (LSTM) networks to analyze multiple frames and incorporate temporal information, ensuring that it performs well even when visual information is limited. We collected data from 126 patients using PillCam™ SB3 (Medtronic, Minneapolis, MN, USA), which comprised 2,395,932 images. Our deep learning model was trained to identify organs (stomach, small intestine, and colon) using data from 44 training and 10 validation cases. We applied calibration using a Gaussian filter to enhance the accuracy of detecting organ boundaries. Additionally, we estimated the transit time of the capsule in the gastric and small intestine regions using a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) designed to be aware of the sequence information of continuous videos. Finally, we evaluated the model's performance using WCE videos from 72 patients. Our model demonstrated high performance in organ classification, achieving an accuracy, sensitivity, and specificity of over 95% for each organ (stomach, small intestine, and colon), with an overall accuracy and F1-score of 97.1%. The Matthews Correlation Coefficient (MCC) and Geometric Mean (G-mean) were used to evaluate the model's performance on imbalanced datasets, achieving MCC values of 0.93 for the stomach, 0.91 for the small intestine, and 0.94 for the colon, and G-mean values of 0.96 for the stomach, 0.95 for the small intestine, and 0.97 for the colon. Regarding the estimation of gastric and small intestine transit times, the mean time differences between the model predictions and ground truth were 4.3 ± 9.7 min for the stomach and 24.7 ± 33.8 min for the small intestine. Notably, the model's predictions for gastric transit times were within 15 min of the ground truth for 95.8% of the test dataset (69 out of 72 cases). The proposed model shows overall superior performance compared to a model using only CNN. The combination of CNN and LSTM proves to be both accurate and clinically effective for organ classification and transit time estimation in WCE. Our model's ability to integrate temporal information allows it to maintain high performance even in challenging conditions where color information alone is insufficient. Including MCC and G-mean metrics further validates the robustness of our approach in handling imbalanced datasets. These findings suggest that the proposed method can significantly improve the diagnostic accuracy and efficiency of WCE, making it a valuable tool in clinical practice for diagnosing and managing GI diseases.

Treatment-free survival and partitioned survival analysis of patients with advanced renal cell carcinoma treated with nivolumab plus ipilimumab versus sunitinib: 5-year update of CheckMate 214

BackgroundImmunotherapy can be associated with prolonged disease control even after cessation of treatment without the need for further cancer-directed therapy. Treatment-related adverse events (TRAEs) can also persist after discontinuation of...

Time-varying effect in older patients with early-stage breast cancer: a model considering the competing risks based on a time scale.

Patients with early-stage breast cancer may have a higher risk of dying from other diseases, making a competing risks model more appropriate. Considering subdistribution hazard ratio, which is used often, limited to model assumptions and clinical interpretation, we aimed to quantify the effects of prognostic factors by an absolute indicator, the difference in restricted mean time lost (RMTL), which is more intuitive. Additionally, prognostic factors of breast cancer may have dynamic effects (time-varying effects) in long-term follow-up. However, existing competing risks regression models only provide a static view of covariate effects, leading to a distorted assessment of the prognostic factor. To address this issue, we proposed a dynamic effect RMTL regression that can explore the between-group cumulative difference in mean life lost over a period of time and obtain the real-time effect by the speed of accumulation, as well as personalized predictions on a time scale. A simulation validated the accuracy of the coefficient estimates in the proposed regression. Applying this model to an older early-stage breast cancer cohort, it was found that 1) the protective effects of positive estrogen receptor and chemotherapy decreased over time; 2) the protective effect of breast-conserving surgery increased over time; and 3) the deleterious effects of stage T2, stage N2, and histologic grade II cancer increased over time. Moreover, from the view of prediction, the mean C-index in external validation reached 0.78. Dynamic effect RMTL regression can analyze both dynamic cumulative effects and real-time effects of covariates, providing a more comprehensive prognosis and better prediction when competing risks exist.

Position prediction of underwater gliders based on a new heterogeneous model ensemble method

An underwater glider (UG) is a promising unmanned underwater vehicle driven by buoyancy that can perform long-period and large-scale ocean observations. Due to the lack of inertial sensors and the low-speed relative to the ocean current, it is difficult to determine the exact position of the UG. Besides, the position of the UG is of great significance for acoustic applications. Therefore, this paper proposes a new heterogeneous model ensemble method (HMEM) based on the whale algorithm (WOA) optimized backpropagation neural network with complement ensemble empirical mode decomposition (CEEMD-BPNN) and the physical model. The physical model can deduce the underwater position of the UG considering the ambient environment, and the WOA-CEEMD-BPNN is adopted to predict the surface position with historical data. Then, the new heterogeneous model ensemble method integrates these two with an unscented Kalman filter according to the predicted surface position. To evaluate the performance of the HMEM, the evaluation index is introduced, and the sea trial conducted by the Petrel-II glider is used as a case study. The experiment demonstrates that the MAE and RMSE of the HMEM are 0.51 km and 0.76 km, respectively, and the mean time difference is 3.08 × 102 s, which outperforms the dynamic model and can achieve accurate position prediction for long periods.

Evaluating the relationship between health-related social needs, patient demographics, and access to biologics in patients with moderate-to-severe asthma in Bronx, NY

Objectives This study assesses the relationship between patient age, gender, race, socioeconomic status, social determinants of health (SDoH), and access to biologics (products isolated from natural sources that target specific molecules, proteins, and cells) in patients with moderate-to-severe asthma in Bronx, NY. Methods Cohort of 289 patients with moderate-to-severe asthma treated at Montefiore Medical Center (MMC) from 2018 to 2020 was used. Patient demographics, self-reported social needs, and neighborhood socioeconomic characteristics were analyzed. Neighborhood socioeconomic status was estimated by determining median income in patients’ residential zip codes using 2020 Census data and grouping patients based on whether neighborhood median income was above or below New York State (NYS) median ($71,117/year). Area Deprivation Index tool (ADI) was used as an additional measure of neighborhood socioeconomic status. Results Patients living in regions with incomes below NYS median found to have longer wait times between biologic approval to administration than patients living in regions above median income (p = 0.012). Mean time from insurance approval to biologic administration was significantly different between Black and Latinx patients (p = 0.009). No significant difference found for patient regional income status and time from biologic prescription to approval. No significant differences in access to biologics were found for age, gender, number of health-related social needs, or patient ADI quartile. Conclusions Patients who live in areas of NYC where median income is below NYS median are more likely to experience delays in access to biologics, specifically due to time between approval and administration of medication.

Pediatric cardiomyopathy illustrates the importance of reinterpreting the significance of genetic variants

BackgroundClinical genetic testing is increasingly being utilized to establish a molecular diagnosis to help manage children with cardiomyopathy and to assess the risk of cardiomyopathy among family members. However, as evidence and guidelines evolve, variant classification can change with the potential to impact counseling and family screening. ObjectivesThe main purpose of this study was to investigate whether variants in cardiomyopathy genes previously interpreted by clinical genetic testing laboratories would be reclassified under current guidelines for the interpretation of sequence variants. MethodsIn 211 children enrolled in the Pediatric Cardiomyopathy Registry, we compared the results of previous clinical genetic testing with the results of research testing in 37 cardiomyopathy genes. ResultsThe mean time difference between initial testing and reinterpretation was 7 years. Using the 2015 American College of Medical Genetics and Genomics guidelines for the interpretation of sequence variants, we found that 18 % of the tested population had a change in variant classification. Ninety-two percent of the initial classifications were performed before the publication of the guidelines, with 82 % of reclassifications resulting in a variant downgrade. Most of these were changes from the pathogenic or likely pathogenic category to a variant of uncertain significance. Reclassification frequency was similar across types of cardiomyopathy. ConclusionOur results highlight that a portion of variants get downgraded, and periodic reinterpretation of genetic testing results is necessary for all types of cardiomyopathy—particularly for variant interpretations prior to 2015. Importantly, variant reclassification has potential impact on the clinical management of at-risk patients.

Bilateral Elimination Rule-Based Finite Class Bayesian Inference System for Circular and Linear Walking Prediction.

The prediction of upcoming circular walking during linear walking is important for the usability and safety of the interaction between a lower limb assistive device and the wearer. This study aims to build a bilateral elimination rule-based finite class Bayesian inference system (BER-FC-BesIS) with the ability to predict the transition between circular walking and linear walking using inertial measurement units. Bilateral motion data of the human body were used to improve the recognition and prediction accuracy of BER-FC-BesIS. The mean predicted time of BER-FC-BesIS in predicting the left and right lower limbs' upcoming steady walking activities is 119.32 ± 9.71 ms and 113.75 ± 11.83 ms, respectively. The mean time differences between the predicted time and the real time of BER-FC-BesIS in the left and right lower limbs' prediction are 14.22 ± 3.74 ms and 13.59 ± 4.92 ms, respectively. The prediction accuracy of BER-FC-BesIS is 93.98%. Upcoming steady walking activities (e.g., linear walking and circular walking) can be accurately predicted by BER-FC-BesIS innovatively. This study could be helpful and instructional to improve the lower limb assistive devices' capabilities of walking activity prediction with emphasis on non-linear walking activities in daily living.

Effect of Random, Blocked, and Mixed Practice Order on Upper Extremity Motor Learning in Subjects with Parkinson’s Disease

Background: Random practice order has been shown to improve motor learning in normal individuals as well as sports players. The purpose of this study is to investigate which practice order is beneficial in subjects with Parkinson’s disease. Methodology: The total number of Subjects included in this study was 32. Blocked practice order followed by random followed by mixed practice order was given. In between washout period of 1 week was given. Response time during acquisition and retention was assessed. Data were analyzed statistically by using one-way ANOVA. Results: The mean time taken by the subjects was maximum with Random practice order with (p=0.001, SD= 10.73) during Acquisition and (p=0.003, SD=8.88). The mean time difference was maximum with random (p= 0.001) in both the acquisitions as well as retention phases. On comparing the difference between the 1st and 10th trials of all three practice orders by using Analysis of Variance (ANOVA) post hoc analysis by using Tukey’s test, we observed that in subjects with PD Random practice order is more beneficial than mixed and blocked respectively. Discussion: On comparing all three practice orders we can infer that Upper Extremity motor learning skill was superior with Random practice orders followed by Mixed and blocked practice orders respectively in both the acquisition and retention phases. KEYWORDS: Parkinson’s Disease, Motor Learning, Practice Order, Acquisition, Retention.

Effectiveness of a grid mattress on adults' sleep quality and health: A quasi-experimental intervention study.

Despite that 93% of people indicate that a mattress plays a pivotal role in achieving high-quality sleep, there is a scarcity of research investigating the influence of mattresses on sleep quality, pain, and mood in nonclinical poor sleepers. The purpose was to examine the effectiveness of a pressure-releasing medium-firm grid mattress on sleep and health outcomes (e.g., mood, pain, daytime fatigue) of adults with nonclinical insomnia symptoms using a quasi-experimental design. Participants were 39 adults (mean age = 45.29) with nonclinical insomnia (i.e., occasional sleeplessness). Following 1 week of baseline assessments on their current mattress, they slept on a pressure-relieving grid mattress for 8 weeks. Participants completed self-report assessments of the Pittsburgh Sleep Quality Index, Berlin Questionnaire, Insomnia Severity Index, Restorative Sleep Questionnaire, Perceived Stress Scale, Profile of Mood States, Daytime Fatigue Scale, Pain and Sleep Questionnaire, and Brief Pain Inventory at Baseline and Weeks 1, 2, 3, 4, and 8. Participants continually wore an Oura Ring to objectively assess sleep and daytime activity. The data were collected from January 2022 to April 2022 and were stored electronically. Repeated-measures analyses of variance were used to analyze mean time differences. Self-reported sleep quality, perceived pain, perceived stress, mood, and daytime fatigue improved significantly from Baseline to Week 8, p's < 0.05. Objective Oura Ring validated the self-reported sleep and daytime activity outcomes with improvements in sleep duration, time awake during the night, light sleep, deep sleep, and total sleep time, p's < 0.05. No significant time effects were evidenced for rapid eye movement sleep. No adverse events were reported. The grid mattress is a simple, noninvasive, and nonpharmacological intervention that improved adults sleep quality and health. Controlled trials are encouraged to examine the effects of this mattress in a variety of populations and environments.

Efficacy and Rapidity of Potassium Hydroxide Mount and Modified Chicago Sky Blue 6B Stain with Potassium Hydroxide in Fungal Keratitis Detection.

To compare the efficacy and rapidity of direct microscopic detection of fungal elements from corneal ulcers between 10% potassium hydroxide (KOH) and 1% Chicago Sky Blue 6B (CSB) in 10% KOH (CSB-KOH). Thirty patients with clinically suspected fungal keratitis were recruited. Participants with impending corneal perforation were excluded. Two slides were smeared with corneal ulcer scrapings from the ulcer's edge and base for comparison of fungal staining solutions. One slide was infused with KOH, and the other slide was filled with CSB-KOH. Additional scraping was collected for inoculation on Sabouraud dextrose agar for fungal culture. The sensitivity, specificity and rapidity of both stainings were analyzed. The sensitivity of fungal culture, KOH, and CSB-KOH were 43.75% (95% confidence interval [CI], 19.75%-70.12%), 62.50% (95% CI, 35.43%-84.80%), and 87.50% (95% CI, 61.65%-98.45%), respectively. The specificity were 100% (95% CI, 69.15%-100%) of both stainings and fungal culture which analyzed from 16 fungal keratitis cases by laboratory and clinical diagnosis. Mean CSB-KOH examination time was quicker than KOH with the mean time difference of 5.6 minutes (95% CI, 3.22-7.98 minutes) and p-value &lt; 0.001. CSB-KOH was more effective and faster than KOH in detecting fungal elements from corneal ulcers. Therefore, CSB-KOH may be beneficial in diagnosing fungal keratitis and preventing blindness. Moreover, to the best of our knowledge, this is the first use of CSB stain in fungal keratitis detection.

Artificial intelligence for ventricular arrhythmia capability using ambulatory electrocardiograms.

European and American clinical guidelines for implantable cardioverter defibrillators are insufficiently accurate for ventricular arrhythmia (VA) risk stratification, leading to significant morbidity and mortality. Artificial intelligence offers a novel risk stratification lens through which VA capability can be determined from the electrocardiogram (ECG) in normal cardiac rhythm. The aim of this study was to develop and test a deep neural network for VA risk stratification using routinely collected ambulatory ECGs. A multicentre case-control study was undertaken to assess VA-ResNet-50, our open source ResNet-50-based deep neural network. VA-ResNet-50 was designed to read pyramid samples of three-lead 24 h ambulatory ECGs to decide whether a heart is capable of VA based on the ECG alone. Consecutive adults with VA from East Midlands, UK, who had ambulatory ECGs as part of their NHS care between 2014 and 2022 were recruited and compared with all comer ambulatory electrograms without VA. Of 270 patients, 159 heterogeneous patients had a composite VA outcome. The mean time difference between the ECG and VA was 1.6 years (⅓ ambulatory ECG before VA). The deep neural network was able to classify ECGs for VA capability with an accuracy of 0.76 (95% confidence interval 0.66-0.87), F1 score of 0.79 (0.67-0.90), area under the receiver operator curve of 0.8 (0.67-0.91), and relative risk of 2.87 (1.41-5.81). Ambulatory ECGs confer risk signals for VA risk stratification when analysed using VA-ResNet-50. Pyramid sampling from the ambulatory ECGs is hypothesized to capture autonomic activity. We encourage groups to build on this open-source model. Can artificial intelligence (AI) be used to predict whether a person is at risk of a lethal heart rhythm, based solely on an electrocardiogram (an electrical heart tracing)? In a study of 270 adults (of which 159 had lethal arrhythmias), the AI was correct in 4 out of every 5 cases. If the AI said a person was at risk, the risk of lethal event was three times higher than normal adults. In this study, the AI performed better than current medical guidelines. The AI was able to accurately determine the risk of lethal arrhythmia from standard heart tracings for 80% of cases over a year away-a conceptual shift in what an AI model can see and predict. This method shows promise in better allocating implantable shock box pacemakers (implantable cardioverter defibrillators) that save lives.

Impact of Stress, Loneliness and Sociodemographic Factors on Psychological Well‐Being During the COVID‐19 Pandemic

AbstractBackgroundPersonal and social factors have had a varied effect on older adults during the COVID‐19 pandemic. Psychosocial factors and underlying pathological changes may have influenced the mental health of these older adults. Understanding the drivers behind the mental health of older adults during the pandemic may help identify treatment targets. We aimed to understand this phenomenon by exploring the relationships between the psychosocial factors iand self‐reported experiences of psychological well‐being.MethodWe included 149 participants (mean age: 75.6) from the Harvard Aging Brain Study and Instrumental Activities of Daily Living Study who took a survey conducted during the Summer of 2021, to assess stress (Perceived Stress Scale), loneliness (UCLA Loneliness Scale. 3‐item version), resilience (Connor Davidson Resilience Scale) and psychological well‐being (PROMIS‐Global Mental), encompassing self‐reported quality of life, mood and thinking, satisfaction with social relationships and anxiety and depressive symptoms. Pre‐assessed measures of cortical amyloid (PiB; mean time difference = 1.8 years) and medial temporal tau (Flortaucipir; mean time difference = 1.7 years) were also included. We performed a hierarchal regression analysis to understand the relationships among the psychosocial factors, controlling for demographics, amyloid, and tau as predictors of well‐being.ResultDemographic and survey responses are presented in Table 1. Significant negative associations were found among perceived well‐being and pathology (amyloid and tau), stress and loneliness, such that increased pathology, increased stress and increased feelings of loneliness were related to worse mental health (Figure 1). A positive association was found between resilience and well‐being, such that increased resilience was related to higher well‐being. (Figure 1). The hierarchical regression analysis results revealed that loneliness (β = −0.32, t = −5.81, p&lt;.001), stress (β = −0.38, t = −5.48, p&lt;.001), and resilience (β = 0.28, t = 4.34, p&lt;.001) uniquely accounted for a significant proportion of variance in well‐being even after controlling for demographic characteristics (age, sex, education, race) and psychosocial characteristics (marital status, living alone) (Table 2).ConclusionOur findings suggest that measuring and quantifying loneliness, stress, and resilience can help clinicians and researchers understand the potential detrimental effects of the COVID‐19 pandemic among older adults. These findings may extend to other prolonged exposures to stressful situations and uncover much needed targets for intervention.

Severe mental illness and symptoms of acute coronary syndrome in emergency calls

Abstract Background It can be lifesaving to act fast and correct when acute life-threatening diseases occur. This is, however, challenging in some patients with severe mental illness as they sometimes experience symptoms differently than patients without severe mental illness. This changed perception can affect the patients’ chances of receiving adequate help, as these patients are already stigmatized even by healthcare personnel. Purpose We aimed to determine whether patients with severe mental illness reported different symptoms of acute coronary syndrome (ACS) in emergency calls than patients without severe mental illness. Methods In this registry-based study, we analyzed symptoms of ACS in emergency calls made from 2014 to 2018 in the Capital Emergency Medical Services, including the Emergency Number (1-1-2) and the Out-of-hours Service (medical helpline). The study population comprised patients with severe mental illness (defined by schizophrenia, bipolar affective disorder, and depression) and a control group of patients without severe mental illness. Additionally, we investigated whether psychotropics (defined by antipsychotics, mood stabilizers, and antidepressants) were associated with altered symptom presentation of ACS. Furthermore, we determined the time from the emergency call to hospitalization. Analyses were performed by logistic regression adjusted for sex and age and t-tests. Results In total, 11,113 emergency calls were included; 917 were from patients with severe mental illness (45.4% were female, average age was 64.6 years), and 10,196 were from patients without severe mental illness (35.3% were female, average age was 67.7 years). Severe mental illness was associated with less frequent chest pain in ACS (odds ratio 0.80, 95%CI: 0.70-0.92, p=0.002). Furthermore, treatment with psychotropics was associated with less frequent chest pain in ACS (odds ratio 0.73, 95%CI: 0.64-0.82, p&amp;lt;0.001). The mean time difference from the emergency call to hospitalization was 17 minutes longer for patients with severe mental illness (1 hour 21 minutes vs. 1 hour 4 minutes, p=0.002) Conclusion Patients with severe mental illness presented less frequent chest pain in ACS in emergency calls than patients without severe mental illness and had increased time to hospitalization. This calls for increased awareness of symptom presentation in patients with severe mental illness to improve the identification and management of ACS.

Abstract 14246: Impact of Coronavirus Disease 2019 Infection on Non-ST Elevation Myocardial Infarction Outcomes

Introduction: In this study, we explore the in-hospital outcomes of non-ST elevation myocardial infarction (NSTEMI) patients with and without concurrent coronavirus disease 2019 (COVID-19) infection. Methods: We utilized the National Inpatient Sample database (2016-2020) to identify patients who were admitted with a principal diagnosis of NSTEMI and a secondary diagnosis of COVID-19 infection. We conducted propensity score matching. Multivariable logistic regression, adjusted for age, sex and comorbidities, was used to compare mortality. Results: 1340 patients met our inclusion criteria. NSTEMI patients with concomitant COVID-19 infection had 3.24 times higher odds of suffering in-hospital mortality compared to NSTEMI admissions without COVID-19 (aOR 3.24, 95% CI: 1.93-5.43; p &lt; 0.001). When separated by race, NSTEMI patients with COVID-19 had higher mortality rates amongst White (8.2% vs 4.7%, p = 0.04) and Black patients (14.2% vs 0.9%, p &lt; 0.001, Figure 1). NSTEMI patients with COVID-19 infection were more likely to have acute respiratory distress syndrome (1.6% vs 0.1%, p = 0.004), myocarditis (1.3% vs 0%, p = 0.003) and severe sepsis (2.8% vs 0.9%, p = 0.01, Table 1). These patients were less likely to undergo percutaneous coronary intervention (PCI) (22.7% vs 28.4%, p = 0.02), but there was no significant difference in mean time to PCI (1.7 days vs 1.3 days, p = 0.12). Conclusion: Patients with NSTEMI and concurrent COVID-19 infection had higher odds of suffering in-hospital mortality compared to NSTEMI patients without COVID-19 infection. Further research should examine the impact of COVID-19 vaccination on the outcomes of this high-risk patient population.

Impact of a ground intermediate transport from the helicopter landing site at a hospital on transport duration and patient safety

BackgroundHelicopter emergency medical service provides timely care and rapid transport of severely injured or critically ill patients. Due to constructional or regulatory provisions at some hospitals, a remote helicopter landing site necessitates an intermediate ground transport to the emergency department by ambulance which might lengthen patient transport time and comprises the risk of disconnection or loss of vascular access lines, breathing tubes or impairment of other relevant equipment during the loading processes. The aim of this study was to evaluate if a ground intermediate transport at the hospital site prolonged patient transport times and operating times or increases complication rates.MethodsA retrospective analysis of all missions of a German air rescue service between 2012 and 2020 was conducted. Need of a ground transport at the accepting hospital, transfer time from the helipad to the hospital, overall patient transport time from the emergency location or the referring hospital to the accepting hospital and duration of the mission were analyzed. Several possible confounders such as type of mission, mechanical ventilation of the patient, use of syringe infusion pumps (SIPs), day- or nighttime were considered.ResultsOf a total of 179,003 missions (92,773 (51,8%) primary rescue missions, 10,001 (5,6%) polytrauma patients) 86,230 (48,2%) secondary transfers) an intermediate transport by ambulance occurred in 40,459 (22,6%) cases. While transfer times were prolonged from 6.3 to 8.8 min for primary rescue cases (p < 0.001) and from 9.2 to 13.5 min for interhospital retrieval missions (p < 0.001), the overall patient transport time was 14.8 versus 15.8 min (p < 0.001) in primary rescue and 23.5 versus 26.8 min (p < 0.001) in interhospital transfer. Linear regression analysis revealed a mean time difference of 3.91 min for mechanical ventilation of a patient (p < 0.001), 7.06 min for the use of SIPs (p < 0.001) and 2.73 min for an intermediate ambulance transfer (p < 0.001). There was no relevant difference of complication rates seen.ConclusionsAn intermediate ground transport from a remote helicopter landing site to the emergency department by ambulance at the receiving hospital had a minor impact on transportation times and complication rates.

Coronary Artery Calcium Identified on Non-Gated Chest CT Scans: A Wasted Opportunity for Preventive Cardiological Care

Coronary artery calcium (CAC) evaluated on dedicated cardiac computed tomography (CT) is an independent predictor of cardiovascular events. This study aimed to evaluate the correlation between CAC detected on non-gated standard chest CT and coronary lesions on coronary angiography (CAG) and determine its impact on prognosis. Consecutive patients who underwent CAG due to acute coronary syndrome and had prior non-contrasted non-gated chest CT were included and retrospectively evaluated. Coronary artery calcium was evaluated by quantitative (Agatston score) and qualitative (visual assessment) assessment. A total of 114 patients were included in this study. The mean time difference between chest CT and CAG was 23 months. Coronary artery calcium was visually classified as mild, moderate, and severe in 31%, 33%, and 16% of patients, respectively. Moderate or severe CAC was an independent predictor of significant lesions on CAG (OR 22; 95% CI 8-61; p<0.001) and all-cause mortality (OR 4; 95% CI 2-9; p=0.001). Quantitative CAC evaluation accurately predicted significant lesions on CAG (AUC 0.81; p<0.001). While significant CAC was identified in 80% of chest CTs, formal reporting was 25%. Coronary artery calcium evaluation with chest CT was feasible and strongly associated with severity of coronary disease on CAG and mortality. Although the identification of CAC on chest CT represents a unique opportunity for cardiovascular risk stratification for preventive care, CAC underreporting is frequent.